Determining the reproductive toxicity risk of compounds is vitally important to ensure the health of the general population. It is a difficult and complex task involving testing in animals. While it is well known that mouse strain background can have a profound effect on phenotype, understanding the role of strain background in toxicity testing remains a tremendous challenge. An in vitro genetic testing system contributes toward this end by offering the advantages of lower cost, higher throughput and no sacrifice of animals in testing. An in vitro genetic system can be a "first tier" testing platform, directing in vivo testing to mouse strains that maximize informativeness and minimize animal use. We propose to develop an in vitro, ES cell based system to assess the impact of genetic background in toxicity testing. ES cells are particularly attractive for this purpose since they can be propagated indefinitely in their pluripotent state while retaining the ability to contribute to all tissues of an animal. In Phase I we demonstrated the feasibility of this system by establishing ES cell lines from six genetically distinct mouse strains and showing that a measurable and significant variability due to genetic background can be measured in response to exposure to a reference compound, retinoic acid. In Phase II, a panel of approximately 100 genetically distinct ES lines will be established and tested with a larger panel of reference compounds, toward the development of a system to define, map and identify the genetic components of cellular response to environmental burden. This system will lead to more predictive reproductive toxicity testing by providing a platform to investigate the role of genetic background on toxicity risk. The testing platform will be made commercially available to the pharmaceutical and chemical industries, as well as to academic institutions. PUBLIC HEALTH RELEVANCE: We propose to develop a system that can help elucidate the role of genetics in reproductive toxicity testing. The broad and varied genetic backgrounds in the proposed testing system better reflects the genetic diversity of the US population, and may lead to more predictive testing that reduces environmental health risk to the population.